Quantum Approximate Optimization With Parallelizable Gates
Open accessAbstract
The quantum approximate optimization algorithm (QAOA) has been introduced as a heuristic digital quantum computing scheme to find approximate solutions of combinatorial optimization problems. We present a scheme to parallelize this approach for arbitrary all-to-all connected problem graphs in a layout of quantum bits (qubits) with nearest-neighbor interactions. The protocol consists of single qubit operations that encode the optimization problem, whereas interactions are problem-independent pairwise CNOT gates among nearest neighbors. This allows for a parallelizable implementation in quantum devices with a planar lattice geometry. The basis of this proposal is a lattice gauge model, which also introduces additional parameters and protocols for QAOA to improve the efficiency.
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The LHZ architecture solves the connectivity issue at the cost of increasing the number of qubits.
“The so-called LHZ architecture is an approach that solves the connectivity issue at the cost of increasing the number of qubits (Lechner, 2020).”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as Lechner, 2020
Several other approaches have been identified where ansatz adaptations happen as a secondary effect.
“Several other approaches have been identified where the ansatz adaptations happen as a secondary effect, e.g., References [36, 48, 82, 131, 153].”
From Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study (2024) · cites this paper as [82]
Lechner presents a novel approach to parallelize QAOA for arbitrary complete graphs that uses single-qubit rather than two-qubit operators to encode the optimization problem.
“Therefore, Lechner [82] presents a novel approach to parallelize QAOA for arbitrary complete graphs that uses single-qubit rather than two-qubit operators to encode the optimization problem.”
From Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study (2024) · cites this paper as [82]
A parallelized version of QAOA is used for the first smart charging problem.
“Whereas a parallelized version of QAOA [82] is used for the first problem, the second one requires a transformation of the original graph into a unitary disk graph to be embeddable on Rydberg QC architectures.”
From Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study (2024) · cites this paper as [82]
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- Authors
- Lechner, W.
- Affiliations
- Universität Innsbruck (AT)
- Corresponding author
- Lechner, Wolfgang
- ORCID
- Lechner, Wolfgang
- Venue
- IEEE Transactions on Quantum Engineering
- Published
- 2020
- Volume
- 1
- Pages
- 1-6
- ISSN
- 2689-1808 (ISSN-L)
- OpenAlex
- W2787503115
- Cited by
- 57
- References
- 39
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 6 · 2023: 12 · 2022: 11 · 2021: 6 · 2020: 7 · 2019: 2 · 2018: 1
- FWCI
- 3.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Transactions on Quantum Engineering (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Funders
- European Commission (HORIZON2020, 817482)
- Austrian Science Fund (Y1067, F7108-N38)
- Universität Innsbruck
- Defense Advanced Research Projects Agency (HR001120C0068)
- Advanced Research Projects Agency
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Keywords
- quantum approximate optimization algorithm, parallelization, combinatorial optimization, CNOT gate, nearest-neighbor interactions
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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